Approximate Bayesian computation (ABC) algorithms are a class of Monte Carlo methods for doing inference when the likelihood function can be simulated from, but not explicitly evaluated. This ...

Approximate Bayesian Computation (ABC) is a likelihood‐free inference methodology that has revolutionised the way researchers tackle complex problems where the likelihood function is difficult or ...

Proceedings of the National Academy of Sciences of the United States of America, Vol. 108, No. 37 (September 13, 2011), pp. 15112-15117 (6 pages) Approximate Bayesian computation (ABC) have become an ...

Abstract: Generator parameter calibration is essential for power system analysis and control. With intractable likelihood function due to complex dependencies between parameters and the simulation ...

ABC (approximate Bayesian computation) is a general approach for dealing with models with an intractable likelihood. In this work, we derive ABC algorithms based on QMC (quasi-Monte Carlo) sequences.

The estimation of parameters in molecular evolution may be biased when some processes are not considered. For example, the estimation of selection at the molecular level using codon-substitution ...

1 Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Mumbai 2 Department of Mathematics, Institute of Chemical Technology, Mumbai Approximate Bayesian Computation ...